{"id":"W1993304237","doi":"10.3934/mbe.2009.6.301","title":"Culling structured hosts to eradicate vector-borne diseases","year":2009,"lang":"en","type":"article","venue":"Mathematical Biosciences & Engineering","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Culling; Vector (molecular biology); Disease control; Differential equation; Applied mathematics; Control theory (sociology); Biology; Mathematics; Toxicology; Computer science; Ecology; Control (management); Artificial intelligence; Biotechnology; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007093608,0.0004660093,0.0005940373,0.0003423406,0.0002650283,0.0007428614,0.001480595,0.0009331173,0.002744971],"category_scores_gemma":[0.00243855,0.0002806297,0.0004446011,0.0002567571,0.0007362966,0.001085342,0.0006091491,0.0006411032,0.0003797701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006630057,"about_ca_system_score_gemma":0.0007620793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003327363,"about_ca_topic_score_gemma":0.003585657,"domain_scores_codex":[0.9997838,0.00006271659,0.00001029307,0.00004621822,0.00002937075,0.00006771936],"domain_scores_gemma":[0.9991853,0.0003772979,0.000212855,0.00006037013,0.00006437199,0.00009989583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001458526,0.00009379951,0.004004791,0.0001334936,0.0000625469,0.0003641479,0.0002353622,0.853224,0.01229234,0.1179926,0.0009142523,0.01053688],"study_design_scores_gemma":[0.00003776385,0.0001438973,0.00072811,0.00001159144,0.00003838903,0.0001129915,0.00004696467,0.9862285,0.000846065,0.01067718,0.001116367,0.00001228943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4833062,0.0004828427,0.5041832,0.001007203,0.0001316934,0.0001054225,0.0003223888,0.0001942002,0.01026672],"genre_scores_gemma":[0.9773995,0.0003173727,0.01292161,0.00007521158,0.00002684853,0.00007000015,0.00006451521,0.00001584133,0.009109286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003327363,"threshold_uncertainty_score":0.00918287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01384375282190303,"score_gpt":0.2701349418275029,"score_spread":0.2562911890055998,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}